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tensorflow/c/experimental/filesystem/plugins/gcs/ram_file_block_cache_test.cc
env->SetNowSeconds(now + 1); TF_EXPECT_OK(ReadCache(&cache, "b", 0, 1, &out)); // Now load a different block of file "a" at timestamp `now` + 1. When the // first block of "a" expires, this block should also be removed because it // also belongs to file "a". TF_EXPECT_OK(ReadCache(&cache, "a", 8, 1, &out)); // Ensure that all blocks are in the cache (i.e. reads are cache hits).
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tensorflow/BUILD
# On MacOS, the linker does not support version_script, but has an # an "-exported_symbols_list" command. -z defs disallows undefined # symbols in object files. tf_cc_shared_object( name = "tensorflow", linkopts = select({ "//tensorflow:macos": [ "-Wl,-exported_symbols_list,$(location //tensorflow/c:exported_symbols.lds)", ], "//tensorflow:windows": [ ],
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tensorflow/c/BUILD
"@com_google_absl//absl/strings", "@local_xla//xla/tsl/c:tsl_status_internal", ], alwayslink = 1, ) exports_files( [ "version_script.lds", "exported_symbols.lds", ], visibility = ["//visibility:public"], ) filegroup( name = "checkpoint_reader_hdrs", srcs = [ "checkpoint_reader.h", "tf_status_helper.h", ],
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SECURITY.md
performance limitations. ## Multi-Tenant environments It is possible to run multiple TensorFlow models in parallel. For example, `ModelServer` collates all computation graphs exposed to it (from multiple `SavedModel`) and executes them in parallel on available executors. Running TensorFlow in a multitenant design mixes the risks described above with the
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tensorflow/c/eager/immediate_execution_context.h
namespace tensorflow { class EagerExecutor; class EagerContext; class CustomDevice; class CustomDeviceOpHandler; class Device; // LINT.IfChange // Note: Keep in sync with exported copy of enum in eager/c_api.h. enum ContextDevicePlacementPolicy { // Running operations with input tensors on the wrong device will fail. DEVICE_PLACEMENT_EXPLICIT = 0,
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Jul 06 08:34:00 GMT 2023 - 12.3K bytes - Viewed (0) -
RELEASE.md
* Correctness fixes for fft_length parameter to `tf.spectral.rfft` & `tf.spectral.irfft`. * Exported model signatures using the 'predict' method will no longer have their input and output keys silently ignored and rewritten to 'inputs' and 'outputs'. If a model was exported with different names before 1.2, and is now served with tensorflow/serving, it will accept requests using 'inputs'
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ci/official/utilities/setup.sh
# "TFCI" may optionally be set to the name of an env-type file with TFCI # variables in it, OR may be left empty if the user has already exported the # relevant variables in their environment. Because of 'set -o allexport' above # (which is equivalent to "set -a"), every variable in the file is exported # for other files to use. # # Separately, if TFCI is set *and* there are also additional TFCI_ variables
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tensorflow/c/c_api.h
// - `inputs` cannot refer to TF_Outputs within a control flow context. For // example, one cannot use the output of "switch" node as input. // - `inputs` and `outputs` cannot have reference types. Reference types are // not exposed through C API and are being replaced with Resources. We support // reference types inside function's body to support legacy code. Do not // use them in new code.
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